Applied AI for Public Health Data Science (online), Master of Professional Studies (M.P.S.)
The MPS in Applied AI for Public Health Data Science requires a total of 30 credits, including 27 credits of required coursework and 3 credits of elective coursework.
| Course | Title | Credits |
|---|---|---|
| SPHL601 | Core Concepts in Public Health | 1 |
| EPIB610 | Foundations of Epidemiology | 3 |
| EPIB650 | Biostatistics I | 3 |
| EPIB651 | Applied Regression Analysis | 3 |
| EPIB695 | Introduction to R for Health Data Analysis | 3 |
| EPIB674 | Statistical Foundations of Machine Learning in Public Health: From Classical to Deep Learning | 3 |
| EPIB667 | (Applied Machine Learning with Python) | 3 |
| EPIBXXX | (Text and Image Analysis in Public Health - new) | 3 |
| EPIBXXX | (AI Ethics in Public Health - new) | 3 |
| EPIBXXX | (Applied AI for Public Health Data Science Research Project - new) | 2 |
| Elective | 3 | |
| Total Credits | 30 | |
The elective course will be selected in consultation with an advisor. Possible elective options include the following courses. This list will expand as the program grows and additional courses relevant to the program are developed across campus.
- EPIB684 Epidemiologic Research Using Electronic Health Records Data
- MSAI606 Human-Centered Participatory Approaches to AI*
- MSAI630 Safe & Trustworthy AI*
- MSAI631 AI and Society*
*Approval for a student to take a particular MSAI course will depend on permission of the MSAI program and seat availability.